1. Field of the Invention
The present invention generally relates to data analysis. More specifically, the present invention relates to discerning human intent based on analysis of user-generated metadata.
2. Description of the Related Art
More than a half billion users generate large amounts of data each day on social media networks such as Twitter®, Facebook®, MySpace®, and Foursquare®. Users from around the globe post photos, videos, text (e.g., status updates and blogs), and other information at exponentially increasing rates. Online social networks have become communication hubs where users exchange information regarding their daily activities, political views, cravings, product complaints, family issues, and general interests and musings.
This user-generated metadata can be harvested and analyzed to detect areas where business can improve the services and products they offer. There presently exists monitoring technology that allows organizations to gather large amounts of metadata from third party services such as micro-blogging, photo sharing, blogging, and other social networking sites. With the aforementioned growth of such social networking sites, however, the sheer amount of meta-data being generated now makes it next to impossible for a human operator to manually review and export aggregated data in a time-efficient manner.
The detection and handling of sales leads, support requests, and product feedback is currently a manual process in which raw data generated from social media networks is individually analyzed, tagged, and exported to a customer relationship management (CRM) or support system by human operators. This process is extremely time-consuming and expensive due to the tremendous amount of information generated each day by social media networks, as well as the amount of human labor required to analyze and process such information. The ability to accurately identify and process this information by manual means alone is nearing a point of impossibility.
There is a need in the art for a system that can be completely automated, intelligent, and aware of different inter-departmental systems within the enterprise where data can be exported for further processing.